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Our client is a leading research-based biopharmaceutical company. They apply science and their global resources to deliver innovative therapies that extend and significantly improve lives. Every day, colleagues work across developed and emerging markets to advance wellness, prevention, reatments and cures that challenge the most feared diseases of our time.
The Enterprise Platforms & Security (EP&S) team delivers the following capabilities for Pfizer – Business application platforms supporting Pfizer’s enterprise application and critical business processes. Infrastructure allowing business traffic to travel where it needs to go, internally and externally, along with the appropriate access controls. EP&S secures Pfizer’s most important information assets through world class controls and protections and enables Pfizer’s business results by making security an enabler and not a roadblock to achieving business results.
As Manager, Data Science, you will be part of a team to develop new capabilities that leverage AI/ML to solve complex problems for the Enterprise Platforms and Security team. You will guide the strategic roadmap for developing new capabilities and help support existing solutions. You will apply AI/ML to support automation use cases as well as predictive modeling to avoid critical issues. The ideal candidate is an expert in data science with experience working in cross-functional teams, bridging the gap between data, technology, and people.
- Work in multi-disciplinary and cross-functional teams to translate business requirements into machine learning based goals and modeling approaches; rapidly iterate model structure and design through parameter tuning, data transformation, and accuracy measurement selection to refine and validate approach.
- Work with large, complex, and structured/unstructured data sets
- Collaborate with Data Integration and Machine Learning Engineers to deliver end-to-end production applications
- Execute advanced analytics and predictive modeling projects using rigorous statistical methods and machine learning techniques
- Design, develop, deploy, and maintain reusable assets and custom pipelines to optimize operational efficiencies in analytics execution
- BS in computer science, data science, or an engineering field.
- 5+ years of experience in data and analytics field
- Strong background in computer science: algorithms, data structures, machine learning, and distributed systems
- Experience with time series analysis and forecasting
- Strong proficiency with Python and PL/SQL and experience with
other programming languages such as R, Java, Scala.
- Effective written and verbal communication skills to translate
technical solutions and methodologies to stakeholders